Understanding Temporal Human Mobility Patterns in a City by Mobile Cellular Data Mining, Case Study: Tehran City

Recent studies have shown that urban complex behaviors like human mobility should be examined by newer and smarter methods. The ubiquitous use of mobile phones and other smart communication devices helps us use a bigger amount of data that can be browsed by the hours of the day, the days of the week, geographic area, meteorological conditions, and so on. In this article, mobile cellular data mining is introduced as an emerging approach in analyzing and understanding human mobility patterns, then generic location update is examined as a way to observe and perceive human mobility and movement in cities. This method was examined in Tehran metropolitan area map, the results show that different urban issues can be understood and solved using this huge amount of data like urban transportation, social problems or urban functions. Tehran cellular data analysis shows that it can be recognized as a city in two major parts, the border zone which is mostly the origin of all trips and the central zone which is mostly the destination of all trips and the most visited hotspot of the city during a normal day, also it was concluded that because of low population density in this part of the city and very high human mobility throughout a day, this area would have many social security issues. In the end, taking advantage of more accurate data in cell level was proposed in order to have better and more reliable assumptions about future mobility trends and co-presence patterns.